Application of neural networks in object recognition tasks for ADAS systems

dc.contributor.author	Ziyatdinov R.
dc.contributor.author	Biktimirov R.
dc.date.accessioned	2020-01-21T20:50:58Z
dc.date.available	2020-01-21T20:50:58Z
dc.date.issued	2019
dc.identifier.issn	1757-8981
dc.identifier.uri	https://dspace.kpfu.ru/xmlui/handle/net/157774
dc.description.abstract	© 2019 IOP Publishing Ltd. All rights reserved. Modern driver assistance systems (ADAS) require an environmental recognition function to inform the driver and for making management decisions. Neural networks are used to select and recognize objects in such systems. The paper presents the results of comparative analysis of various neural networks in object recognition problems. Experimental data showed that convolutional neural networks show the best results in recognition problems.
dc.relation.ispartofseries	IOP Conference Series: Materials Science and Engineering
dc.title	Application of neural networks in object recognition tasks for ADAS systems
dc.type	Conference Paper
dc.relation.ispartofseries-issue	1
dc.relation.ispartofseries-volume	570
dc.collection	Публикации сотрудников КФУ
dc.source.id	SCOPUS17578981-2019-570-1-SID85072059649

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Публикации сотрудников КФУ Scopus [24551]
Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.